National and Subnational estimates for the United States of America

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally in the United States of America. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Table of Contents


Using data available up to the: 2020-04-03

Expected daily cases by region


Figure 1: The results of the latest reproduction number estimates (based on estimated cases with a date of infection on the 2020-03-23) in the United States of America, stratified by state, can be summarised by whether cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Regions with fewer than 40 cases reported on a single day are not included in the analysis (light grey).

National summary

Summary (estimates as of the 2020-03-23)

Table 1: Latest estimates (as of the 2020-03-23) of the number of cases by date of infection, the expected change in daily cases, the effective reproduction number, the doubling time, and the adjusted R-squared of the exponential fit. The mean and 90% credible interval is shown for each numeric estimate.
Estimate
New cases by infection date 26659 (15125 – 36534)
Expected change in daily cases Likely increasing
Effective reproduction no. 1.4 (1 – 1.8)
Doubling time (days) 11 (5.4 – 250)
Adjusted R-squared 0.7 (0.14 – 1)

Reported cases, their estimated date of infection, and time-varying reproduction number estimates


Figure 2: A.) Cases by date of report (bars) and their estimated date of infection. B.) Time-varying estimate of the effective reproduction number. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Estimates are shown until the 2020-03-23.Dark grey ribbon = 50% credible interval. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Time-varying rate of spread and doubling time


Figure 3: A.) Time-varying estimate of the rate of spread, B.) Time-varying estimate of the doubling time in days (note that when the rate of spread is negative the doubling time is assumed to be infinite), C.) The adjusted R-squared estimates indicating the goodness of fit of the exponential regression model (with values closer to 1 indicating a better fit). Estimates are shown until the 2020-03-23. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Regional Breakdown

Data availability

Limitations

Summary of latest reproduction number and case count estimates by date of infection


Figure 4: Cases with date of infection on the 2020-03-23 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily cases and shaded based on the expected change in daily cases. The dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most incident cases


Figure 5: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of incident cases. Estimates are shown up to the 2020-03-23. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported cases and their estimated date of infection in the six regions expected to have the most incident cases


Figure 6: Cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of incident cases. Estimates are shown up to the 2020-03-23. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Reproduction numbers over time in all regions


Figure 7: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-03-23. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported cases and their estimated date of infection in all regions

Figure 8: Cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-03-23. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Latest estimates (as of the 2020-03-23)

Table 2: Latest estimates (as of the 2020-03-23) of the number of cases by date of infection, the effective reproduction number, and the doubling time in each region. The mean and 90% credible interval is shown.
State New cases by infection date Expected change in daily cases Effective reproduction no. Doubling time (days)
Alabama 1405 (575 – 2268) Increasing 1.7 (0.9 – 2.4) 6.2 (3.2 – 210)
Alaska 185 (59 – 283) Likely increasing 1.7 (0.9 – 2.5) 6.7 (3.2 – Inf)
Arizona 1321 (819 – 1755) Increasing 1.6 (1.1 – 2) 7 (4.2 – 20)
Arkansas 744 (240 – 1128) Likely increasing 1.6 (0.8 – 2.1) 8.1 (3.9 – Inf)
California 8696 (5609 – 11775) Increasing 1.5 (1.1 – 1.9) 8.1 (4.7 – 28)
Colorado 3665 (1850 – 5638) Increasing 1.6 (1 – 2.2) 6.7 (3.6 – 39)
Connecticut 3786 (1489 – 6054) Increasing 1.8 (1 – 2.6) 5.4 (2.8 – 35)
Delaware 411 (138 – 683) Likely increasing 1.7 (0.9 – 2.4) 6.4 (3.2 – 250)
District of Columbia 650 (271 – 1028) Increasing 1.6 (0.9 – 2.3) 7.1 (3.5 – 2800)
Florida 7821 (3921 – 11676) Increasing 1.7 (1 – 2.3) 6 (3.4 – 27)
Georgia 4579 (2154 – 6960) Increasing 1.7 (1 – 2.3) 6.6 (3.5 – 48)
Guam 165 (43 – 290) Likely increasing 1.9 (0.8 – 2.9) 5.5 (2.6 – Inf)
Hawaii 286 (104 – 422) Likely increasing 1.6 (0.9 – 2.3) 7.2 (3.6 – Inf)
Idaho 729 (178 – 1209) Increasing 2 (1 – 3) 4.8 (2.5 – 37)
Illinois 6228 (4170 – 8519) Increasing 1.6 (1.1 – 2) 7 (4.3 – 17)
Indiana 2629 (1018 – 3820) Increasing 1.8 (1.1 – 2.7) 5.4 (3 – 32)
Iowa 627 (251 – 963) Increasing 1.8 (1 – 2.5) 5.8 (3.1 – 63)
Kansas 541 (215 – 868) Increasing 1.7 (1 – 2.5) 6 (3.1 – 120)
Kentucky 732 (298 – 1111) Increasing 1.7 (1 – 2.4) 6.2 (3.2 – 54)
Louisiana 6807 (2747 – 10802) Increasing 1.7 (0.9 – 2.4) 6.1 (3.2 – 120)
Maine 419 (166 – 673) Likely increasing 1.6 (0.9 – 2.3) 7.1 (3.5 – Inf)
Maryland 2078 (832 – 3142) Increasing 1.8 (1 – 2.5) 5.7 (3.1 – 32)
Massachusetts 6889 (4414 – 9503) Increasing 1.6 (1.1 – 2) 6.4 (3.9 – 18)
Michigan 9956 (3642 – 15656) Increasing 1.8 (1 – 2.5) 5.7 (3 – 52)
Minnesota 777 (332 – 1187) Likely increasing 1.5 (1 – 2.2) 8 (3.9 – Inf)
Mississippi 1259 (441 – 1982) Likely increasing 1.7 (0.8 – 2.3) 6.7 (3.3 – Inf)
Missouri 1666 (724 – 2495) Increasing 1.8 (1 – 2.5) 5.6 (3.1 – 30)
Montana 279 (90 – 435) Likely increasing 1.7 (0.9 – 2.6) 6.1 (2.9 – Inf)
Nebraska 223 (114 – 324) Increasing 1.5 (1.1 – 2) 7.9 (4.2 – 78)
Nevada 1434 (698 – 2282) Likely increasing 1.7 (1 – 2.4) 6.4 (3.3 – 130)
New Hampshire 440 (210 – 661) Increasing 1.7 (1 – 2.3) 6.6 (3.6 – 46)
New Jersey 22175 (11301 – 35318) Increasing 1.7 (1 – 2.5) 5.8 (3.1 – 35)
New Mexico 426 (164 – 692) Increasing 1.7 (0.9 – 2.5) 6.5 (3.2 – Inf)
New York 88819 (44415 – 133337) Likely increasing 1.6 (1 – 2.2) 7.6 (4 – 230)
North Carolina 1795 (882 – 2675) Increasing 1.6 (1 – 2.3) 6.6 (3.6 – 61)
North Dakota 172 (55 – 268) Likely increasing 1.7 (0.9 – 2.5) 6.3 (3.1 – Inf)
Ohio 2902 (1092 – 4524) Increasing 1.8 (1 – 2.5) 5.8 (3.1 – 46)
Oklahoma 711 (300 – 1094) Increasing 1.7 (1 – 2.4) 6 (3.2 – 54)
Oregon 792 (389 – 1132) Increasing 1.6 (1 – 2.1) 7.4 (3.9 – 110)
Pennsylvania 6110 (2090 – 9348) Increasing 1.8 (0.9 – 2.5) 5.4 (3 – 35)
Puerto Rico 306 (105 – 525) Increasing 2 (0.9 – 3) 4.7 (2.5 – 59)
Rhode Island 562 (248 – 855) Increasing 1.8 (1 – 2.5) 5.8 (3.2 – 43)
South Carolina 1337 (551 – 2014) Increasing 1.7 (1 – 2.4) 6.6 (3.4 – 260)
South Dakota 148 (51 – 232) Increasing 1.7 (1 – 2.5) 6.1 (3.2 – 180)
Tennessee 2497 (1184 – 3964) Increasing 1.6 (1 – 2.3) 6.9 (3.6 – 69)
Texas 3823 (2406 – 5397) Increasing 1.6 (1.1 – 2.1) 6.9 (4.1 – 22)
Utah 1041 (529 – 1527) Increasing 1.6 (1 – 2.2) 7.2 (3.9 – 53)
Vermont 366 (142 – 557) Likely increasing 1.6 (0.9 – 2.2) 7.4 (3.5 – Inf)
Virginia 1526 (640 – 2287) Increasing 1.7 (0.9 – 2.4) 6.2 (3.2 – 48)
Washington 5684 (3716 – 7896) Increasing 1.4 (1 – 1.7) 11 (5.7 – 85)
West Virginia 249 (63 – 409) Likely increasing 1.9 (0.9 – 2.9) 5.3 (2.7 – 350)
Wisconsin 1504 (887 – 2018) Increasing 1.5 (1 – 1.9) 8.8 (4.9 – 35)
Wyoming 155 (58 – 256) Increasing 1.7 (0.9 – 2.4) 6.8 (3.2 – Inf)

“2019 Novel Coronavirus Covid-19 (2019-nCoV) Data Repository.” 2020. Johns Hopkins CSSE. https://github.com/CSSEGISandData/COVID-19.

Abbott, Sam, Joel Hellewell, James D. Munday, and Sebastian Funk. 2020. “NCoVUtils: Utility Functions for the 2019-Ncov Outbreak.” - - (-): –. https://doi.org/10.5281/zenodo.3635417.

Xu, Bo, Bernardo Gutierrez, Sarah Hill, Samuel Scarpino, Alyssa Loskill, Jessie Wu, Kara Sewalk, et al. n.d. “Epidemiological Data from the nCoV-2019 Outbreak: Early Descriptions from Publicly Available Data.” http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/337.

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